mirror of
https://github.com/timescale/timescaledb.git
synced 2025-05-22 05:31:41 +08:00
f071f89ade
This change fixes issues in the shared `dist_chunk` test that caused flakiness. Since the test shares a database and state with other tests running in parallel, it should modify the database (e.g., creating new tables and chunks) while the test runs. Such modifications will cause non-deterministic behavior that varies depending on the order the tests are run in. To fix this issue, all the table creations have been moved into the shared setup script and the test itself has been made less dependent on hard-coded IDs and chunk names. One of the tables used in the has been changed to use space-partitioning to make chunk placement on nodes more predictible.
244 lines
13 KiB
SQL
244 lines
13 KiB
SQL
-- This file and its contents are licensed under the Timescale License.
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-- Please see the included NOTICE for copyright information and
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-- LICENSE-TIMESCALE for a copy of the license.
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SET client_min_messages TO ERROR;
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SET ROLE :ROLE_DEFAULT_PERM_USER;
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CREATE SCHEMA test;
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-- create normal hypertable with dropped columns, each chunk will have different attribute numbers
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CREATE TABLE metrics(filler_1 int, filler_2 int, filler_3 int, time timestamptz NOT NULL, device_id int, v0 int, v1 int, v2 float, v3 float);
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CREATE INDEX ON metrics(time DESC);
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CREATE INDEX ON metrics(device_id,time DESC);
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SELECT create_hypertable('metrics','time',create_default_indexes:=false);
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ALTER TABLE metrics DROP COLUMN filler_1;
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INSERT INTO metrics(time,device_id,v0,v1,v2,v3) SELECT time, device_id, device_id+1, device_id + 2, device_id + 0.5, NULL FROM generate_series('2000-01-01 0:00:00+0'::timestamptz,'2000-01-05 23:55:00+0','2m') gtime(time), generate_series(1,5,1) gdevice(device_id);
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ALTER TABLE metrics DROP COLUMN filler_2;
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INSERT INTO metrics(time,device_id,v0,v1,v2,v3) SELECT time, device_id, device_id-1, device_id + 2, device_id + 0.5, NULL FROM generate_series('2000-01-06 0:00:00+0'::timestamptz,'2000-01-12 23:55:00+0','2m') gtime(time), generate_series(1,5,1) gdevice(device_id);
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ALTER TABLE metrics DROP COLUMN filler_3;
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INSERT INTO metrics(time,device_id,v0,v1,v2,v3) SELECT time, device_id, device_id, device_id + 2, device_id + 0.5, NULL FROM generate_series('2000-01-13 0:00:00+0'::timestamptz,'2000-01-19 23:55:00+0','2m') gtime(time), generate_series(1,5,1) gdevice(device_id);
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ANALYZE metrics;
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-- create identical hypertable with space partitioning
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CREATE TABLE metrics_space(filler_1 int, filler_2 int, filler_3 int, time timestamptz NOT NULL, device_id int, v0 int, v1 int, v2 float, v3 float);
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CREATE INDEX ON metrics_space(time);
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CREATE INDEX ON metrics_space(device_id,time);
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SELECT create_hypertable('metrics_space','time','device_id',3,create_default_indexes:=false);
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ALTER TABLE metrics_space DROP COLUMN filler_1;
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INSERT INTO metrics_space(time,device_id,v0,v1,v2,v3) SELECT time, device_id, device_id+1, device_id + 2, device_id + 0.5, NULL FROM generate_series('2000-01-01 0:00:00+0'::timestamptz,'2000-01-05 23:55:00+0','2m') gtime(time), generate_series(1,5,1) gdevice(device_id);
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ALTER TABLE metrics_space DROP COLUMN filler_2;
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INSERT INTO metrics_space(time,device_id,v0,v1,v2,v3) SELECT time, device_id, device_id+1, device_id + 2, device_id + 0.5, NULL FROM generate_series('2000-01-06 0:00:00+0'::timestamptz,'2000-01-12 23:55:00+0','2m') gtime(time), generate_series(1,5,1) gdevice(device_id);
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ALTER TABLE metrics_space DROP COLUMN filler_3;
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INSERT INTO metrics_space(time,device_id,v0,v1,v2,v3) SELECT time, device_id, device_id+1, device_id + 2, device_id + 0.5, NULL FROM generate_series('2000-01-13 0:00:00+0'::timestamptz,'2000-01-19 23:55:00+0','2m') gtime(time), generate_series(1,5,1) gdevice(device_id);
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ANALYZE metrics_space;
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-- create hypertable with compression
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CREATE TABLE metrics_compressed(filler_1 int, filler_2 int, filler_3 int, time timestamptz NOT NULL, device_id int, v0 int, v1 int, v2 float, v3 float);
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CREATE INDEX ON metrics_compressed(time);
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CREATE INDEX ON metrics_compressed(device_id,time);
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SELECT create_hypertable('metrics_compressed','time',create_default_indexes:=false);
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ALTER TABLE metrics_compressed DROP COLUMN filler_1;
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INSERT INTO metrics_compressed(time,device_id,v0,v1,v2,v3) SELECT time, device_id, device_id+1, device_id + 2, device_id + 0.5, NULL FROM generate_series('2000-01-01 0:00:00+0'::timestamptz,'2000-01-05 23:55:00+0','2m') gtime(time), generate_series(1,5,1) gdevice(device_id);
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ALTER TABLE metrics_compressed DROP COLUMN filler_2;
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INSERT INTO metrics_compressed(time,device_id,v0,v1,v2,v3) SELECT time, device_id, device_id-1, device_id + 2, device_id + 0.5, NULL FROM generate_series('2000-01-06 0:00:00+0'::timestamptz,'2000-01-12 23:55:00+0','2m') gtime(time), generate_series(1,5,1) gdevice(device_id);
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ALTER TABLE metrics_compressed DROP COLUMN filler_3;
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INSERT INTO metrics_compressed(time,device_id,v0,v1,v2,v3) SELECT time, device_id, device_id, device_id + 2, device_id + 0.5, NULL FROM generate_series('2000-01-13 0:00:00+0'::timestamptz,'2000-01-19 23:55:00+0','2m') gtime(time), generate_series(1,5,1) gdevice(device_id);
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ANALYZE metrics_compressed;
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-- compress chunks
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ALTER TABLE metrics_compressed SET (timescaledb.compress, timescaledb.compress_orderby='time DESC', timescaledb.compress_segmentby='device_id');
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SELECT compress_chunk(c.schema_name|| '.' || c.table_name)
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FROM _timescaledb_catalog.chunk c, _timescaledb_catalog.hypertable ht where c.hypertable_id = ht.id and ht.table_name = 'metrics_compressed' and c.compressed_chunk_id IS NULL
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ORDER BY c.table_name DESC;
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-- create hypertable with space partitioning and compression
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CREATE TABLE metrics_space_compressed(filler_1 int, filler_2 int, filler_3 int, time timestamptz NOT NULL, device_id int, v0 int, v1 int, v2 float, v3 float);
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CREATE INDEX ON metrics_space_compressed(time);
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CREATE INDEX ON metrics_space_compressed(device_id,time);
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SELECT create_hypertable('metrics_space_compressed','time','device_id',3,create_default_indexes:=false);
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ALTER TABLE metrics_space_compressed DROP COLUMN filler_1;
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INSERT INTO metrics_space_compressed(time,device_id,v0,v1,v2,v3) SELECT time, device_id, device_id+1, device_id + 2, device_id + 0.5, NULL FROM generate_series('2000-01-01 0:00:00+0'::timestamptz,'2000-01-05 23:55:00+0','2m') gtime(time), generate_series(1,5,1) gdevice(device_id);
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ALTER TABLE metrics_space_compressed DROP COLUMN filler_2;
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INSERT INTO metrics_space_compressed(time,device_id,v0,v1,v2,v3) SELECT time, device_id, device_id+1, device_id + 2, device_id + 0.5, NULL FROM generate_series('2000-01-06 0:00:00+0'::timestamptz,'2000-01-12 23:55:00+0','2m') gtime(time), generate_series(1,5,1) gdevice(device_id);
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ALTER TABLE metrics_space_compressed DROP COLUMN filler_3;
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INSERT INTO metrics_space_compressed(time,device_id,v0,v1,v2,v3) SELECT time, device_id, device_id+1, device_id + 2, device_id + 0.5, NULL FROM generate_series('2000-01-13 0:00:00+0'::timestamptz,'2000-01-19 23:55:00+0','2m') gtime(time), generate_series(1,5,1) gdevice(device_id);
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ANALYZE metrics_space_compressed;
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-- compress chunks
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ALTER TABLE metrics_space_compressed SET (timescaledb.compress, timescaledb.compress_orderby='time DESC', timescaledb.compress_segmentby='device_id');
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SELECT compress_chunk(c.schema_name|| '.' || c.table_name)
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FROM _timescaledb_catalog.chunk c, _timescaledb_catalog.hypertable ht where c.hypertable_id = ht.id and ht.table_name = 'metrics_space_compressed' and c.compressed_chunk_id IS NULL
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ORDER BY c.table_name DESC;
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RESET ROLE;
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-- Add data nodes
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SELECT * FROM add_data_node('data_node_1', host => 'localhost', database => 'data_node_1');
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SELECT * FROM add_data_node('data_node_2', host => 'localhost', database => 'data_node_2');
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SELECT * FROM add_data_node('data_node_3', host => 'localhost', database => 'data_node_3');
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GRANT USAGE ON FOREIGN SERVER data_node_1, data_node_2, data_node_3 TO PUBLIC;
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SET ROLE :ROLE_DEFAULT_PERM_USER;
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CREATE TABLE metrics_dist(filler_1 int, filler_2 int, filler_3 int, time timestamptz NOT NULL, device_id int, v0 int, v1 int, v2 float, v3 float);
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SELECT create_distributed_hypertable('metrics_dist','time','device_id',3);
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ALTER TABLE metrics_dist DROP COLUMN filler_1;
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INSERT INTO metrics_dist(time,device_id,v0,v1,v2,v3) SELECT time, device_id, device_id+1, device_id + 2, device_id + 0.5, NULL FROM generate_series('2000-01-01 0:00:00+0'::timestamptz,'2000-01-05 23:55:00+0','2m') gtime(time), generate_series(1,5,1) gdevice(device_id);
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ALTER TABLE metrics_dist DROP COLUMN filler_2;
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INSERT INTO metrics_dist(time,device_id,v0,v1,v2,v3) SELECT time, device_id, device_id+1, device_id + 2, device_id + 0.5, NULL FROM generate_series('2000-01-06 0:00:00+0'::timestamptz,'2000-01-12 23:55:00+0','2m') gtime(time), generate_series(1,5,1) gdevice(device_id);
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ALTER TABLE metrics_dist DROP COLUMN filler_3;
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INSERT INTO metrics_dist(time,device_id,v0,v1,v2,v3) SELECT time, device_id, device_id+1, device_id + 2, device_id + 0.5, NULL FROM generate_series('2000-01-13 0:00:00+0'::timestamptz,'2000-01-19 23:55:00+0','2m') gtime(time), generate_series(1,5,1) gdevice(device_id);
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ANALYZE metrics_dist;
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-- Tables for gapfill and distributed gapfill tests
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CREATE TABLE gapfill_plan_test(time timestamptz NOT NULL, value float);
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SELECT create_hypertable('gapfill_plan_test','time',chunk_time_interval=>'4 weeks'::interval);
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INSERT INTO gapfill_plan_test SELECT generate_series('2018-01-01'::timestamptz,'2018-04-01'::timestamptz,'1m'::interval), 1.0;
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CREATE TABLE metrics_int(
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time int NOT NULL,
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device_id int,
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sensor_id int,
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value float);
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INSERT INTO metrics_int VALUES
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(-100,1,1,0.0),
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(-100,1,2,-100.0),
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(0,1,1,5.0),
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(5,1,2,10.0),
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(100,1,1,0.0),
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(100,1,2,-100.0);
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CREATE TABLE devices(device_id INT, name TEXT);
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INSERT INTO devices VALUES (1,'Device 1'),(2,'Device 2'),(3,'Device 3');
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CREATE TABLE sensors(sensor_id INT, name TEXT);
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INSERT INTO sensors VALUES (1,'Sensor 1'),(2,'Sensor 2'),(3,'Sensor 3');
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CREATE TABLE insert_test(id INT);
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INSERT INTO insert_test SELECT time_bucket_gapfill(1,time,1,5) FROM (VALUES (1),(2)) v(time) GROUP BY 1 ORDER BY 1;
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CREATE TABLE metrics_tstz(time timestamptz, device_id INT, v1 float, v2 int);
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SELECT create_hypertable('metrics_tstz','time');
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INSERT INTO metrics_tstz VALUES
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(timestamptz '2018-01-01 05:00:00 PST', 1, 0.5, 10),
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(timestamptz '2018-01-01 05:00:00 PST', 2, 0.7, 20),
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(timestamptz '2018-01-01 05:00:00 PST', 3, 0.9, 30),
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(timestamptz '2018-01-01 07:00:00 PST', 1, 0.0, 0),
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(timestamptz '2018-01-01 07:00:00 PST', 2, 1.4, 40),
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(timestamptz '2018-01-01 07:00:00 PST', 3, 0.9, 30)
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;
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CREATE TABLE conditions(
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time timestamptz NOT NULL,
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device int,
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value float
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);
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SELECT * FROM create_hypertable('conditions', 'time');
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INSERT INTO conditions VALUES
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('2017-01-01 06:01', 1, 1.2),
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('2017-01-01 09:11', 3, 4.3),
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('2017-01-01 08:01', 1, 7.3),
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('2017-01-02 08:01', 2, 0.23),
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('2018-07-02 08:01', 87, 0.0),
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('2018-07-01 06:01', 13, 3.1),
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('2018-07-01 09:11', 90, 10303.12),
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('2018-07-01 08:01', 29, 64);
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CREATE TABLE conditions_dist(
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time timestamptz NOT NULL,
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device int,
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value float
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);
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SELECT * FROM create_distributed_hypertable('conditions_dist', 'time', 'device', 3);
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INSERT INTO conditions_dist VALUES
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('2017-01-01 06:01', 1, 1.2),
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('2017-01-01 09:11', 3, 4.3),
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('2017-01-01 08:01', 1, 7.3),
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('2017-01-02 08:01', 2, 0.23),
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('2018-07-02 08:01', 87, 0.0),
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('2018-07-01 06:01', 13, 3.1),
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('2018-07-01 09:11', 90, 10303.12),
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('2018-07-01 08:01', 29, 64);
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CREATE TABLE metrics_int_dist(
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time int NOT NULL,
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device_id int,
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sensor_id int,
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value float);
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SELECT create_distributed_hypertable('metrics_int_dist','time','device_id',chunk_time_interval => 50);
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INSERT INTO metrics_int_dist VALUES
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(-100,1,1,0.0),
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(-100,1,2,-100.0),
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(0,1,1,5.0),
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(5,1,2,10.0),
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(100,1,1,0.0),
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(100,1,2,-100.0);
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CREATE TABLE conditions_dist1(
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time timestamptz NOT NULL,
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device int,
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value float
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);
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SELECT * FROM create_distributed_hypertable('conditions_dist1', 'time', 'device', 1,
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data_nodes => '{"data_node_1"}');
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INSERT INTO conditions_dist1 VALUES
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('2017-01-01 06:01', 1, 1.2),
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('2017-01-01 09:11', 3, 4.3),
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('2017-01-01 08:01', 1, 7.3),
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('2017-01-02 08:01', 2, 0.23),
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('2018-07-02 08:01', 87, 0.0),
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('2018-07-01 06:01', 13, 3.1),
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('2018-07-01 09:11', 90, 10303.12),
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('2018-07-01 08:01', 29, 64);
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CREATE TABLE metrics_int_dist1(
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time int NOT NULL,
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device_id int,
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sensor_id int,
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value float);
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SELECT create_distributed_hypertable('metrics_int_dist1', 'time', 'device_id', chunk_time_interval => 50,
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data_nodes => '{"data_node_1"}');
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INSERT INTO metrics_int_dist1 VALUES
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(-100,1,1,0.0),
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(-100,1,2,-100.0),
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(0,1,1,5.0),
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(5,1,2,10.0),
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(100,1,1,0.0),
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(100,1,2,-100.0);
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-- Create distributed hypertable for copy chunk test. Need to have
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-- a space-dimension to have more predictible chunk placement.
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CREATE TABLE dist_chunk_copy (
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time timestamptz NOT NULL,
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device integer,
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value integer);
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SELECT create_distributed_hypertable('dist_chunk_copy', 'time', 'device', replication_factor => 2);
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ALTER TABLE dist_chunk_copy SET (timescaledb.compress);
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SELECT setseed(0);
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INSERT INTO dist_chunk_copy
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SELECT t, ceil(_timescaledb_internal.get_partition_hash(t)::int % 5), random() * 20
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FROM generate_series('2020-01-01'::timestamp, '2020-01-25'::timestamp, '1d') t;
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-- Compress a few chunks of this dist_chunk_copy hypertable
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SELECT compress_chunk('_timescaledb_internal._dist_hyper_15_68_chunk');
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SELECT compress_chunk('_timescaledb_internal._dist_hyper_15_70_chunk');
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CREATE TABLE mvcp_hyper (time bigint NOT NULL, value integer);
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SELECT table_name FROM create_distributed_hypertable('mvcp_hyper', 'time',
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chunk_time_interval => 200, replication_factor => 3);
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-- Enable compression so that we can test dropping of compressed chunks
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ALTER TABLE mvcp_hyper SET (timescaledb.compress, timescaledb.compress_orderby='time DESC');
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INSERT INTO mvcp_hyper SELECT g, g FROM generate_series(0,1000) g;
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